Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Effects of nutrition on digestión efficiency and gaseous emissions from slurry in growing pigs: III. Influence of varying the dietary level of calcium soap of palm fatty acids distillate with or without orange pulp supplemention

The aim of this study was to establish the relationships between faecal fat concentration and gaseous emissions from pig slurry. Five diets were designed to meet essential nutrient requirements: a control and four experimental feeds including two levels (35 or 70 g/kg) of calcium soap fatty acids distillate (CSP) and 0 or 200 g/kg of orange pulp (OP) combined in a 2 × 2 factorial structure. Thirty growing pigs (six per treatment) were used to measure dry matter (DM) and N balance, coefficients of total tract apparent digestibility (CTTAD) of nutrients, faecal and urine composition and potential emissions of ammonia (NH3) and methane (CH4). Increasing dietary CSP level decreased DM, ether extract (EE) and crude protein (CP) CTTAD (by 4.0, 11.1 and 3.5%, respectively, P < 0.05), but did not influence those of fibrous constituents. It also led to a decrease (from 475 to 412 g/kg DM, P < 0.001) of faecal concentration of neutral detergent fibre (aNDFom) and to an increment (from 138 to 204 g/kg, P < 0.001) of EE in faecal DM that was related to greater CH4 emissions, both per gram of organic matter (P = 0.021) or on a daily basis (P < 0.001). Level of CSP did not affect N content in faeces or urine, but increased daily DM (P < 0.001), and N (P = 0.031) faecal excretion with no effect on urine N excretion. This resulted in lesser (P = 0.036) NH3 potential emission per kg of slurry. Addition of OP decreased CTTAD of EE (by 7.9%, P = 0.044), but increased (P < 0.05) that of all the fibrous fractions. As a consequence, faecal EE content increased (from 165 to 177 g/kg DM; P = 0.012), and aNDFom decreased greatly (from 483 to 404 g/kg DM, P < 0.001), which in all resulted in a lack of effect of OP on CH4 potential emission. Inclusion of OP in the diet also led to a significant decrease of CP CTTAD (by 6.85%, P < 0.001), and to an increase of faecal CP concentration (from 174 to 226 g/kg DM, P < 0.001), with no significant influence on urine N content. These effects resulted in higher N faecal losses, especially those of the undigested dietary origin, without significant effects on potential NH3 emission. No significant interactions between CSP and OP supplementation were observed for the gaseous emissions measured.

Optimizing the reliability and resource efficiency of MapReduce-based systems

Debido al gran incremento de datos digitales que ha tenido lugar en los últimos años, ha surgido un nuevo paradigma de computación paralela para el procesamiento eficiente de grandes volúmenes de datos. Muchos de los sistemas basados en este paradigma, también llamados sistemas de computación intensiva de datos, siguen el modelo de programación de Google MapReduce. La principal ventaja de los sistemas MapReduce es que se basan en la idea de enviar la computación donde residen los datos, tratando de proporcionar escalabilidad y eficiencia. En escenarios libres de fallo, estos sistemas generalmente logran buenos resultados. Sin embargo, la mayoría de escenarios donde se utilizan, se caracterizan por la existencia de fallos. Por tanto, estas plataformas suelen incorporar características de tolerancia a fallos y fiabilidad. Por otro lado, es reconocido que las mejoras en confiabilidad vienen asociadas a costes adicionales en recursos. Esto es razonable y los proveedores que ofrecen este tipo de infraestructuras son conscientes de ello. No obstante, no todos los enfoques proporcionan la misma solución de compromiso entre las capacidades de tolerancia a fallo (o de manera general, las capacidades de fiabilidad) y su coste. Esta tesis ha tratado la problemática de la coexistencia entre fiabilidad y eficiencia de los recursos en los sistemas basados en el paradigma MapReduce, a través de metodologías que introducen el mínimo coste, garantizando un nivel adecuado de fiabilidad. Para lograr esto, se ha propuesto: (i) la formalización de una abstracción de detección de fallos; (ii) una solución alternativa a los puntos únicos de fallo de estas plataformas, y, finalmente, (iii) un nuevo sistema de asignación de recursos basado en retroalimentación a nivel de contenedores. Estas contribuciones genéricas han sido evaluadas tomando como referencia la arquitectura Hadoop YARN, que, hoy en día, es la plataforma de referencia en la comunidad de los sistemas de computación intensiva de datos. En la tesis se demuestra cómo todas las contribuciones de la misma superan a Hadoop YARN tanto en fiabilidad como en eficiencia de los recursos utilizados. ABSTRACT Due to the increase of huge data volumes, a new parallel computing paradigm to process big data in an efficient way has arisen. Many of these systems, called dataintensive computing systems, follow the Google MapReduce programming model. The main advantage of these systems is based on the idea of sending the computation where the data resides, trying to provide scalability and efficiency. In failure-free scenarios, these frameworks usually achieve good results. However, these ones are not realistic scenarios. Consequently, these frameworks exhibit some fault tolerance and dependability techniques as built-in features. On the other hand, dependability improvements are known to imply additional resource costs. This is reasonable and providers offering these infrastructures are aware of this. Nevertheless, not all the approaches provide the same tradeoff between fault tolerant capabilities (or more generally, reliability capabilities) and cost. In this thesis, we have addressed the coexistence between reliability and resource efficiency in MapReduce-based systems, looking for methodologies that introduce the minimal cost and guarantee an appropriate level of reliability. In order to achieve this, we have proposed: (i) a formalization of a failure detector abstraction; (ii) an alternative solution to single points of failure of these frameworks, and finally (iii) a novel feedback-based resource allocation system at the container level. Finally, our generic contributions have been instantiated for the Hadoop YARN architecture, which is the state-of-the-art framework in the data-intensive computing systems community nowadays. The thesis demonstrates how all our approaches outperform Hadoop YARN in terms of reliability and resource efficiency.

Effect of Sb on the quantum efficiency of GaInP solar cells

The energy bandgap of GaInP solar cells can be tuned by modifying the degree of order of the alloy. In this study, we employed Sb to increase the energy bandgap of the GaInP and analyzed its impact on the performance of GaInP solar cells. An effective change in the cutoff wavelength of the external quantum efficiency of GaInP solar cells and an effective increase of 50 mV in the open-circuit voltage of GaInP/Ga(In)As/Ge triple junction solar cells were obtained with the use of Sb. Copyright © 2016 John Wiley & Sons, Ltd.

Irrigation efficiency and water-policy implications for river-basin resilience

Rising demand for food, fiber, and biofuels drives expanding irrigation withdrawals from surface water and groundwater. Irrigation efficiency and water savings have become watchwords in response to climate-induced hydrological variability, increasing freshwater demand for other uses including ecosystem water needs, and low economic productivity of irrigation compared to most other uses. We identify three classes of unintended consequences, presented here as paradoxes. Ever-tighter cycling of water has been shown to increase resource use, an example of the efficiency paradox. In the absence of effective policy to constrain irrigated-area expansion using "saved water", efficiency can aggravate scarcity, deteriorate resource quality, and impair river basin resilience through loss of flexibility and redundancy. Water scarcity and salinity effects in the lower reaches of basins (symptomatic of the scale paradox) may partly be offset over the short-term through groundwater pumping or increasing surface water storage capacity. However, declining ecological flows and increasing salinity have important implications for riparian and estuarine ecosystems and for non-irrigation human uses of water including urban supply and energy generation, examples of the sectoral paradox. This paper briefly considers three regional contexts with broadly similar climatic and water-resource conditions – central Chile, southwestern US, and south-central Spain – where irrigation efficiency directly influences basin resilience. The comparison leads to more generic insights on water policy in relation to irrigation efficiency and emerging or overdue needs for environmental protection.

A Wireless Charging System Applying Phase-Shift and Amplitude Control to Maximize Efficiency and Extractable Power

Wireless power transfer (WPT) is an emerging technology with an increasing number of potential applications to transfer power from a transmitter to a mobile receiver over a relatively large air gap. However, its widespread application is hampered due to the relatively low efficiency of current Wireless power transfer (WPT) systems. This study presents a concept to maximize the efficiency as well as to increase the amount of extractable power of a WPT system operating in nonresonant operation. The proposed method is based on actively modifying the equivalent secondary-side load impedance by controlling the phase-shift of the active rectifier and its output voltage level. The presented hardware prototype represents a complete wireless charging system, including a dc-dc converter which is used to charge a battery at the output of the system. Experimental results are shown for the proposed concept in comparison to a conventional synchronous rectification approach. The presented optimization method clearly outperforms state-of-the-art solutions in terms of efficiency and extractable power.

The Ti plasmid increases the efficiency of Agrobacterium tumefaciens as a recipient in virB-mediated conjugal transfer of an IncQ plasmid

The T-DNA transfer apparatus of Agrobacterium tumefaciens mediates the delivery of the T-DNA into plant cells, the transfer of the IncQ plasmid RSF1010 into plant cells, and the conjugal transfer of RSF1010 between Agrobacteria. We show in this report that the Agrobacterium-to-Agrobacterium conjugal transfer efficiencies of RSF1010 increase dramatically if the recipient strain, as well as the donor strain, carries a wild-type Ti plasmid and is capable of vir gene expression. Investigation of possible mechanisms that could account for this increased efficiency revealed that the VirB proteins encoded by the Ti plasmid were required. Although, with the exception of VirB1, all of the proteins that form the putative T-DNA transfer apparatus (VirB1–11, VirD4) are required for an Agrobacterium strain to serve as an RSF1010 donor, expression of only a subset of these proteins is required for the increase in conjugal transfer mediated by the recipient. Specifically, VirB5, 6, 11, and VirD4 are essential donor components but are dispensable for the increased recipient capacity. Defined point mutations in virB9 affected donor and recipient capacities to the same relative extent, suggesting that similar functions of VirB9 are important in both of these contexts.

Specific mutations in a viral RNA pseudoknot drastically change ribosomal frameshifting efficiency

Many viruses regulate protein synthesis by −1 ribosomal frameshifting using an RNA pseudoknot. Frameshifting is vital for viral reproduction. Using the information gained from the recent high-resolution crystal structure of the beet western yellow virus pseudoknot, a systematic mutational analysis has been carried out in vitro and in vivo. We find that specific nucleotide tertiary interactions at the junction between the two stems of the pseudoknot are crucial. A triplex is found between stem 1 and loop 2, and triplex interactions are required for frameshifting function. For some mutations, loss of one hydrogen bond is sufficient to abolish frameshifting. Furthermore, mutations near the 5′ end of the pseudoknot can increase frameshifting by nearly 300%, possibly by modifying ribosomal contacts. It is likely that the selection of suitable mutations can thus allow viruses to adjust frameshifting efficiencies and thereby regulate protein synthesis in response to environmental change.

High phosphorylation efficiency and depression of uncoupled respiration in mitochondria under hypoxia

Mitochondria are confronted with low oxygen levels in the microenvironment within tissues; yet, isolated mitochondria are routinely studied under air-saturated conditions that are effectively hyperoxic, increase oxidative stress, and may impair mitochondrial function. Under hypoxia, on the other hand, respiration and ATP supply are restricted. Under these conditions of oxygen limitation, any compromise in the coupling of oxidative phosphorylation to oxygen consumption could accentuate ATP depletion, leading to metabolic failure. To address this issue, we have developed the approach of oxygen-injection microcalorimetry and ADP-injection respirometry for evaluating mitochondrial function at limiting oxygen supply. Whereas phosphorylation efficiency drops during ADP limitation at high oxygen levels, we show here that oxidative phosphorylation is more efficient at low oxygen than at air saturation, as indicated by higher ratios of ADP flux to total oxygen flux at identical submaximal rates of ATP synthesis. At low oxygen, the proton leak and uncoupled respiration are depressed, thus reducing maintenance energy expenditure. This indicates the importance of low intracellular oxygen levels in avoiding oxidative stress and protecting bioenergetic efficiency.

Antioxidative Defense System, Pigment Composition, and Photosynthetic Efficiency in Two Wheat Cultivars Subjected to Drought1

We analyzed antioxidative defenses, photosynthesis, and pigments (especially xanthophyll-cycle components) in two wheat (Triticum durum Desf.) cultivars, Adamello and Ofanto, during dehydration and rehydration to determine the difference in their sensitivities to drought and to elucidate the role of different protective mechanisms against oxidative stress. Drought caused a more pronounced inhibition in growth and photosynthetic rates in the more sensitive cv Adamello compared with the relatively tolerant cv Ofanto. During dehydration the glutathione content decreased in both wheat cultivars, but only cv Adamello showed a significant increase in glutathione reductase and hydrogen peroxide-glutathione peroxidase activities. The activation states of two sulfhydryl-containing chloroplast enzymes, NADP+-dependent glyceraldehyde-3-phosphate dehydrogenase and fructose-1,6-bisphosphatase, were maintained at control levels during dehydration and rehydration in both cultivars. This indicates that the defense systems involved are efficient in the protection of sulfhydryl groups against oxidation. Drought did not cause significant effects on lipid peroxidation. Upon dehydration, a decline in chlorophyll a, lutein, neoxanthin, and β-carotene contents, and an increase in the pool of de-epoxidized xanthophyll-cycle components (i.e. zeaxanthin and antheraxanthin), were evident only in cv Adamello. Accordingly, after exposure to drought, cv Adamello showed a larger reduction in the actual photosystem II photochemical efficiency and a higher increase in nonradiative energy dissipation than cv Ofanto. Although differences in zeaxanthin content were not sufficient to explain the difference in drought tolerance between the two cultivars, zeaxanthin formation may be relevant in avoiding irreversible damage to photosystem II in the more sensitive cultivar.

The level of mRNA encoding the amphotropic retrovirus receptor in mouse and human hematopoietic stem cells is low and correlates with the efficiency of retrovirus transduction.

The low level of amphotropic retrovirus-mediated gene transfer into human hematopoietic stem cells (HSC) has been a major impediment to gene therapy for hematopoietic diseases. In the present study, we have examined amphotropic retrovirus receptor (amphoR) and ecotropic retrovirus receptor mRNA expression in highly purified populations of mouse and human HSC. Murine HSC with low to undetectable levels of amphoR mRNA and relatively high levels of ecotropic retrovirus receptor mRNA were studied. When these HSC were analyzed simultaneously for ecotropic and amphotropic retrovirus transduction, ecotropic provirus sequences were detected in 10 of 13 long-term repopulated animals, while amphotropic proviral sequences were detected in only one recipient. A second distinct population of murine HSC were isolated that express 3-fold higher levels of amphoR mRNA. When these HSC were analyzed simultaneously for ecotropic and amphotropic retrovirus transduction, 11 of 11 repopulated mice contained ecotropic provirus and 6 of 11 contained amphotropic provirus sequences, a significant increase in the amphotropic retrovirus transduction (P = 0.018). These results indicate that, among the heterogeneous populations of HSC present in adult mouse bone marrow, the subpopulation with the highest level of amphoR mRNA is more efficiently transduced by amphotropic retrovirus. In a related study, we found low levels of human amphoR mRNA in purified populations of human HSC (CD34+ CD38-) and higher levels in committed progenitor cells (CD34+ CD38+). We conclude that the amphoR mRNA level in HSC correlates with amphotropic retrovirus transduction efficiency.

Orchestration of energy efficiency capabilities for a sustainable network management

The energy demand for operating Information and Communication Technology (ICT) systems has been growing, implying in high operational costs and consequent increase of carbon emissions. Both in datacenters and telecom infrastructures, the networks represent a significant amount of energy spending. Given that, there is an increased demand for energy eficiency solutions, and several capabilities to save energy have been proposed. However, it is very dificult to orchestrate such energy eficiency capabilities, i.e., coordinate or combine them in the same network, ensuring a conflict-free operation and choosing the best one for a given scenario, ensuring that a capability not suited to the current bandwidth utilization will not be applied and lead to congestion or packet loss. Also, there is no way in the literature to do this taking business directives into account. In this regard, a method able to orchestrate diferent energy eficiency capabilities is proposed considering the possible combinations and conflicts among them, as well as the best option for a given bandwidth utilization and network characteristics. In the proposed method, the business policies specified in a high-level interface are refined down to the network level in order to bring highlevel directives into the operation, and a Utility Function is used to combine energy eficiency and performance requirements. A Decision Tree able to determine what to do in each scenario is deployed in a Software Defined Network environment. The proposed method was validated with diferent experiments, testing the Utility Function, checking the extra savings when combining several capabilities, the decision tree interpolation and dynamicity aspects. The orchestration proved to be valid to solve the problem of finding the best combination for a given scenario, achieving additional savings due to the combination, besides ensuring a conflict-free operation.

Carbon assimilation, herbage accumulation, nutritive value, and grazing efficiency of Mulato II brachiariagrass under continuous stocking

Grazed pastures are the backbone of the Brazilian livestock industry and grasses of the genus Brachiaria (syn. Urochloa) are some of most used tropical forages in the country. Although the dependence on the forage resource is high, grazing management is often empirical and based on broad and non-specific guidelines. Mulato II brachiariagrass (Convert HD 364, Dow AgroSciences, São Paulo, Brazil) (B. brizantha × B. ruziziensis × B. decumbens), a new Brachiaria hybrid, was released as an option for a broad range of environmental conditions. There is no scientific information on specific management practices for Mulato II under continuous stocking in Brazil. The objectives of this research were to describe and explain variations in carbon assimilation, herbage accumulation (HA), plant-part accumulation, nutritive value, and grazing efficiency (GE) of Mulato II brachiariagrass as affected by canopy height and growth rate, the latter imposed by N fertilization rate, under continuous stocking. An experiment was carried out in Piracicaba, SP, Brazil, during two summer grazing seasons. The experimental design was a randomized complete block, with a 3 x 2 factorial arrangement, corresponding to three steady-state canopy heights (10, 25 and 40 cm) maintained by mimicked continuous stocking and two growth rates (imposed as 50 and 250 kg N ha-1 yr-1), with three replications. There were no height × N rate interactions for most of the responses studied. The HA of Mulato II increased linearly (8640 to 13400 kg DM ha-1 yr-1), the in vitro digestible organic matter (IVDOM) decreased linearly (652 to 586 g kg-1), and the GE decreased (65 to 44%) as canopy height increased. Thus, although GE and IVDOM were greatest at 10 cm height, HA was 36% less for the 10- than for the 40-cm height. The leaf carbon assimilation was greater for the shortest canopy (10 cm), but canopy assimilation was less than in taller canopies, likely a result of less leaf area index (LAI). The reductions in HA, plant-part accumulation, and LAI, were not associated with other signs of stand deterioration. Leaf was the main plant-part accumulated, at a rate that increased from 70 to 100 kg DM ha-1 d-1 as canopy height increased from 10 to 40 cm. Mulato II was less productive (7940 vs. 13380 kg ha-1 yr-1) and had lesser IVDOM (581 vs. 652 g kg-1) at the lower N rate. The increase in N rate affected plant growth, increasing carbon assimilation, LAI, rates of plant-part accumulation (leaf, stem, and dead), and HA. The results indicate that the increase in the rate of dead material accumulation due to more N applied is a result of overall increase in the accumulation rates of all plant-parts. Taller canopies (25 or 40 cm) are advantageous for herbage accumulation of Mulato II, but nutritive value and GE was greater for 25 cm, suggesting that maintaining ∼25-cm canopy height is optimal for continuously stocked Mulato II.

Portfolio efficiency tests with conditioning information using empirical likelihood estimation

We evaluate the use of Generalized Empirical Likelihood (GEL) estimators in portfolios efficiency tests for asset pricing models in the presence of conditional information. Estimators from GEL family presents some optimal statistical properties, such as robustness to misspecification and better properties in finite samples. Unlike GMM, the bias for GEL estimators do not increase as more moment conditions are included, which is expected in conditional efficiency analysis. We found some evidences that estimators from GEL class really performs differently in small samples, where efficiency tests using GEL generate lower estimates compared to tests using the standard approach with GMM. With Monte Carlo experiments we see that GEL has better performance when distortions are present in data, especially under heavy tails and Gaussian shocks.

An Evaluation of Applicant Tracking Systems for Recruiting Efficiency

The very purpose of a recruiting software program is to help the management of organizations, primarily the HR department to keep track of the job applications. An applicant tracking system can reduce an organization's overall recruitment cost, increase productivity, and raise the level of satisfaction due to faster and better completion of transactions and services. This project analyzes four software providers to discover an applicant tracking system which best suits an organization's recruiting needs. The capstone also highlights that great success an organization can be achieved by significantly improving the delivery of its recruiting services to employees, managers and applicants. The adoption of a well managed applicant tracking system can support this goal.